package com.atguigu.agent.config;

import com.atguigu.agent.store.MongoChatMemoryStore;
import dev.langchain4j.data.document.Document;
import dev.langchain4j.data.document.loader.FileSystemDocumentLoader;
import dev.langchain4j.data.document.splitter.DocumentByParagraphSplitter;
import dev.langchain4j.data.segment.TextSegment;
import dev.langchain4j.memory.chat.ChatMemoryProvider;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.embedding.EmbeddingModel;
import dev.langchain4j.rag.content.retriever.ContentRetriever;
import dev.langchain4j.rag.content.retriever.EmbeddingStoreContentRetriever;
import dev.langchain4j.store.embedding.EmbeddingStore;
import dev.langchain4j.store.embedding.EmbeddingStoreIngestor;
import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

import java.util.Arrays;
import java.util.List;

@Configuration
public class XiaozhiAgentConfig {

    //持久化存储
    @Autowired
    private MongoChatMemoryStore mongoChatMemoryStore;

    @Bean
    public ChatMemoryProvider chatMemoryProviderXiaozhi() {
        return memoryId->
            MessageWindowChatMemory.builder()
                    .id(memoryId)
                    .maxMessages(20)
                    .chatMemoryStore(mongoChatMemoryStore)
                    .build();


    }

/*   @Bean
    ContentRetriever contentRetrieverXiaozhi() {
        //使用FileSystemDocumentLoader读取指定目录下的知识库文档
        //并使用默认的文档解析器对文档进行解析
        Document document1= FileSystemDocumentLoader.loadDocument("D:/Study/java/agentknowledge/医院信息.md");
        Document document2=FileSystemDocumentLoader.loadDocument("D:/Study/java/agentknowledge/科室信息.md");
        Document document3=FileSystemDocumentLoader.loadDocument("D:/Study/java/agentknowledge/神经内科.md");
        List<Document> documents= Arrays.asList(document1,document2,document3);



        //使用内存向量存储
        InMemoryEmbeddingStore<TextSegment> embeddingStore = new InMemoryEmbeddingStore<>();
       //使用默认的文档分割器
       EmbeddingStoreIngestor.ingest(documents, embeddingStore);

        return EmbeddingStoreContentRetriever.from(embeddingStore);
    }
*/
    @Autowired
    private EmbeddingStore embeddingStore;

    @Autowired
    private EmbeddingModel embeddingModel;

    @Bean
    ContentRetriever contentRetrieverXiaozhiPincone(){
        return EmbeddingStoreContentRetriever.builder()
                .embeddingModel(embeddingModel)
                .embeddingStore(embeddingStore)
                .maxResults(1)
                .minScore(0.8)
                .build();
    }





}
